Research Scientist, Market Algorithms, Google Research

Google Research is seeking a Research Scientist to join their Market Algorithms team, focusing on the intersection of microeconomics, algorithms, and machine learning. This role offers an exciting opportunity to design economically and computationally efficient marketplaces across Google's ecosystem, from Ad Auctions to Platform Ecosystems.

The position combines cutting-edge research with real-world impact, allowing you to conduct fundamental research while directly influencing product development. You'll work on challenges that define modern technology, publishing your findings in top-tier conferences and collaborating with product teams to implement solutions that affect billions of users.

As a Research Scientist, you'll be responsible for conducting research in mechanism design, auctions, optimization, game theory, and machine learning. The role involves practical algorithm design, data analysis, and simulations, requiring both theoretical understanding and practical implementation skills. You'll have the opportunity to publish in prestigious conferences like EC, SODA, NeurIPS, and ICML, while engaging with the broader research community.

Google Research provides an environment that encourages innovation and collaboration, with access to vast computational resources and datasets. The company offers competitive compensation, including a strong base salary range of $136,000-$200,000, plus bonus, equity, and comprehensive benefits. You'll be part of an organization that values sharing research and tools to advance the field, regularly publishing in academic journals and releasing open-source projects.

The ideal candidate should have a PhD in Computer Science or related fields, experience with scientific publications, and strong coding skills. This role offers the perfect blend of academic research and practical impact, making it an excellent opportunity for those passionate about advancing the field of market algorithms while working on real-world applications at scale.